get.ab                  Hyperparameter estimation for 'a' and 'b'.
get.alpha               Hyperparameter estimation for 'alpha'.
get.beta                Obtain model coefficient without assuming prior
                        on structure of predictors.
get.beta.ising          Obtain a regression coefficient when assuming
                        Ising prior (with structured predictors).
get.pseudodata.binomial
                        Obtain pseudodata based on the binary logistic
                        regression model.
get.pseudodata.cox      Obtain pseudodata based on the Cox's regression
                        model.
get.sigma               Standard deviation estimation.
get.wpost               Estimate posterior probability of mixing
                        weight.
get.wprior              Mixing weight estimation.
get.zeta                Local posterior probability estimation
get.zeta.ising          Local posterior probability estimation.
icmm                    Empirical Bayes Variable Selection
icmm-package            Empirical Bayes Variable Selection via ICM/M
initbetaBinomial        Initial values for the regression coefficients
                        used in example for running ICM/M algorithm in
                        binary logistic model
initbetaCox             Initial values for the regression coefficients
                        used in example for running ICM/M algorithm in
                        Cox's model
initbetaGaussian        Initial values for the regression coefficients
                        used in example for running ICM/M algorithm in
                        normal linear regression model
linearrelation          Linear structure of predictors
simBinomial             Simulated data from the binary logistic
                        regression model
simCox                  Simulated data from Cox's regression model
simGaussian             Simulated data from the normal linear
                        regression model
